HSBC and Silent Eight Announce Multi-Year Partnership to Fight Financial Crime

New Alert Resolution capability set for implementation within HSBC’s global compliance organization

[London, 06 January 2021] Silent Eight today announced a multi-year partnership with HSBC that will support the bank in enhancing its industry-leading compliance operations. A recognized leader in technology innovation, HSBC sought a financial crime partner that could successfully improve its manual processes and existing statistical models to decrease risk while simultaneously increasing efficiency.

Silent Eight Alert Resolution investigates, and resolves cases in the same way an analyst would; with greater speed, precision and consistency. Following a successful trial period, the solution is set to be integrated into HSBC’s existing infrastructure to provide case adjudications that are explained and auditable.

“Given the growth in alert volumes, and unpredictable spikes driven by global volatility, we saw an opportunity with Silent Eight that would give us the ability to close alerts quickly and accurately,” said HSBC’s Group Head of Compliance Services, Matt Brown.

Silent Eight CEO and co-founder, Martin Markiewicz, said, “We’re delighted to find a partner that shares our focus on eliminating financial crime. HSBC’s dedication to this project is just one aspect of their tireless commitment to improvement, and to helping drive AI innovation across the industry. We’re proud to partner with them on their mission to make the world safer.”

“Silent Eight’s business case was extremely compelling,” said Ben Rayner, HSBC’s Global Head of AML and Sanctions Screening. “We have chosen their solution as we believe it will provide significant business benefits across all our success metrics.”

About Silent Eight: Silent Eight is a technology company leveraging AI to create custom compliance models for the world’s leading financial institutions. Our mission is to empower our clients in their fight to eliminate financial crime. Founded in Singapore and with global hubs in New York, London, and Warsaw, we are deployed in over 150 markets. For more information, visit:

What should you consider when evaluating AI solutions?

A banking insider’s guide to the 5 questions you should ask (and why).

After almost a decade working in a large, global bank, I can speak to the challenges faced by all three lines of defense in trying to combat financial crime. I can also attest to the effect these processes had on our clients.  As a front-line corporate relationship manager, I frequently had to navigate the KYC, remediation and payment screening process for my clients. 

Not only was this an incredibly time consuming and frustrating process on an organizational level, but more painful was the deleterious effect it had on our clients and their business: crucial payments to vendors were delayed unnecessarily, accounts took months to open, and required incessant back and forth between multiple parties, and account fundings/transactions always came down to the wire because of basic due diligence, regardless how much work you tried to do ahead of time.

Much of the process that required our intervention seemed mundane, repetitive and inefficient, which compounded everyone’s frustration. 

Sound familiar?

These types of repetitive, mundane tasks are ideally suited to be outsourced to artificial intelligence, which the industry seems to now realize. 

Artificial intelligence can be an incredibly valuable tool, in that it can offload mundane tasks, provide insight into customer and employee behaviour, create more standardization, and help reduce or manage costs.

But as technology becomes increasingly sophisticated, there are many factors to weigh in the decision making process. 

After countless conversations with stakeholders and decision makers in the industry, I have learned that there are 5 main concerns when implementing regulatory technology, especially AI technology, in the financial sector.  

I’ve outlined them below, along with why they matter:

  1. How transparent is the AI? 
  2. What if the AI learns the wrong behaviours, such as bias?  
  3. Does it have more than one purpose? What is the roadmap?
  4. Is it better than what I have now? More accurate, faster, more standardized, more cost effective? Can ‘better’ be tested quantifiably?
  5. What are the redundancies? How will this technology affect my operational resiliency?

Let’s look at each point in order. 

1. How transparent is the AI? 

While this seems like a straightforward question, “transparent” really encompasses three separate factors:  

  1. Will my team and our stakeholders be able to understand how it works? 
  2. Will I be able to easily demonstrate to Audit, the Board and regulators that it’s doing what it’s supposed to do?
  3. Can I get a snapshot of what is happening at any given moment? 

All of the major regulators have stipulated that artificial intelligence solutions be explainable and demonstrable. Both of these concepts are rather self-explanatory but still worth exploring.


It’s not sufficient for your compliance team to understand how the AI makes decisions. They also need to be comfortable explaining the process to key stakeholders, whether they are board members, the internal model committee, audit, or the regulators. 

If your technical team can’t understand the technology or how decisions are made, or if the vendor claims confidentiality to protect their IP, this is a cause for concern.


Like transparency, demonstrability captures a few components – it means you have to be able to demonstrate:

This is where an audit trail comes into play. First of all, is there one? And if so, is it immutable, and does it capture all actions in the AI or just some of them? Is it exportable in report format and, if so, is the report readable and can it be easily understood?

Compliance is a data-driven world, and the risk associated with being deemed non-compliant is substantial. Being able to capture and export changes to, and decisions made within your AI is crucial to your relationships with your stakeholders.

As personal liability expands in the corporate world, board members and committees increasingly require an understanding of not only how compliance risk is being mitigated, but also clear evidence that it’s being done, how and by whom.

2. What if the AI learns the wrong behaviours, such as bias?

The underlying questions here, without detracting from the very serious concern about embedding existing unconscious bias into your AI, are as follows:

  1. If the AI is wrong, or my requirements change, can I fix it? How easily? 
  2. What impact will tweaking the AI have on everything it’s already learned?

An industry journalist recently asked me if I thought bias was a problem with AI. My answer to her, and to all of you, is that AI simply learns what’s already happening within your organization. As a result, unconscious bias is one of the things that AI can learn, but it doesn’t have to be a problem. 

While you can’t really prevent AI from learning from past decisions (that’s kind of the point), good technology should enable you to identify when it’s learned something wrong, and to tweak it easily to prevent bad decision-making from becoming embedded into your AI’s decision making.

This ties in to the need for transparency and reporting.  It’s not only necessary to see how decisions are made, you also need to be able to prevent poor decisions or bias from being part of the AI’s education. And all of these things need to be documented. 

When testing out new vendors, once the AI engine has been trained initially for your proof of concept, you should be able to clearly understand the findings, and be able to make changes at that time (and thereafter). You will very likely be surprised by some of the ways decisions are currently being made within your organization. 

For example, at Silent Eight, our technology investigates and solves name and transaction alerts for banks. This work is typically done by teams of analysts, who investigate these alerts, and close them as either a true positive (there is risk here) or false positive (there is no risk).  True positive alerts require substantially more time to investigate and close than alerts deemed to be false positive. 

Analysts typically have KPIs around the number of alerts they’re expected to investigate and close each week. 

By late Friday, the analysts are doing everything they can to make sure they meet this quota. As a result, it’s not unusual during the AI training process that the AI learns that 4pm on Fridays is a great reason to close out pending alerts as false positives. 

Obviously this is a good example of AI learning the wrong behaviour and needing to be tweaked. It’s also a good example of mistaking correlation with causation, which is a topic worthy of its own examination on another day.

Today, as regulations are introduced and amended, you’re continually updating your policies to reflect these changes. It’s no different with artificial intelligence.  It’s imperative that your AI engine is correspondingly easy to tweak, and that when you tweak it, you don’t lose everything it has already learned. 

Thoughtful, well architected technology should be built in a manner that makes it easy to update or amend part of the AI engine, without impacting the rest of the learnings.  This is something you should both ask about, and test in the POV environment.

3. Does the AI have more than one purpose? What is the roadmap?

Many financial institutions have the duelling mandates to be both innovative and transform digitally, but also rationalize vendors. So, when considering artificial intelligence solutions, which are often niche, it’s worthwhile finding out:

This way you can ensure that the decision you’re making is one that is future-proofed and set up for longevity.

4. Is it better than what you have now? 

Better can mean different things to different organizations and individuals. It’s typically tied into the problems you’re experiencing now, and what your organization’s strategic focus and priorities are.  When I ask clients and prospects what they mean by ‘better’ the answers I hear most commonly are:

Once you’ve defined what ‘better’ means to you and your organization, you need to find out from your prospective vendors if and how ‘better’ can be tested quantifiably. 

5. What are the third party dependencies? How will this technology affect my operational resiliency?

Operational resiliency and third party due diligence have become a significant focus in the industry and can be a barrier to doing business.  Many regulators, including the EBA and the FCA, have issued guidelines on the topic, and continue to revisit it

It’s vital to understand if a vendor is reliant on any other vendors in their tech stack, if they’re using open source code, what their deployment is (on premise, in the cloud, in a private cloud), and what security standards they adhere to.

Take back the things you can control 

Right now, the financial services industry is beset by many challenges that are outside of its control, including the low interest environment, working remotely, bad debt provisions, and the increased new accounts and suspicious activity resulting from COVID. 

Your compliance costs and processes are a piece of the puzzle you can control.  Good artificial intelligence technology will enable you to offload some of your mundane, repetitive tasks, freeing up you and your team to focus on more complex risks and higher value projects. 

I recognize that artificial intelligence can be a bit daunting, and that it has a mixed reputation in the industry.  However, if you’re armed with a dose of skepticism, the right questions to ask, and you approach it with an open mind, you’ll be amazed by what it can do.


About Amber:  

Amber Sutherland has over fifteen years experience in finance, business development, and regulatory technology. She worked for a large global bank for a decade, and has experienced first hand the evolution banks go through in their digital transformation and compliance journeys. This experience led her to move to regulatory technology, where she helped a former client enter the UK market. She then joined Silent Eight to help enter the EMEA market and grow their business in EMEA and APAC. Silent Eight is an AI-based name, entity and transaction adjudication solution provider to financial institutions. 

Amber’s passionate about finance, technology and trying to prevent criminals from benefiting from their crimes. In her spare time, you will find her on the ski hill. She is currently SVP of Sales, EMEA & APAC for Silent Eight. Follow her on Linked in. LinkedIn.

Silent Eight: Innovative Leaders in RegTech

With offices around the world, Silent Eight leverages AI to help banks and financial institutions combat money laundering and terrorist financing. Given the years of experience and success supporting them, we profiled Silent Eight to learn more about how they earned themselves the reputation as one of the most innovative AI-powered RegTech companies operating in the industry today.

Since their inception in 2013, Silent Eight has been on a mission to protect the world from those that use the financial system to conduct criminal activity, such as money laundering, terrorist financing, and human or animal trafficking. As the team first embarked upon this unique mission, they created an enterprise search solution to help AML investigators in banks find the information and data they needed in order to conduct their investigations faster.

Progressing in their commitment to their mission, Silent Eight went on to build an AI solution that behaves like a human investigator,which is the suite of AI solutions the firm currently has todayand includes name, entity and transaction alert solving. In 2018, Standard Chartered Bank (SCB) was the very first customer that adopted the solution across their entire footprint, including over 60 regulator-approved markets. After using Silent Eight’s AI for a little over a year, SCB participated in their series A funding and even furthered their investment with the firm.

Today, the key to Silent Eight’s remarkable success is that their innovative solution is both intelligent and simple, which has proven to be a winning combination for the firm. The solution seamlessly works within an organization’s existing case management system, conducting and solving alert investigations in English or a company’s preferred language. As such, the solution operates exactly like a company’s best analyst, at all times, and with complete transparency.

Working within the competitive technology landscape, Silent Eight has emerged as a pioneer in the financial crime compliance space. They achieved this by recognizing common challenges in the compliance space, namely using manual labor alone as a solution and relying on statistical methods that rely on risk weighting and scoring. Neither is an approach that Silent Eight believe is a successful model.

With regards to manual labor, the firm believe that it is not an easily scalable solution and presents a number of opportunities for mistakes that can subject a bank to risk and heavy penalties (in the forms of fines and/or reputational damage). Statistical methods are similar as they rely on suppression, which also does not eliminate the possibility of a mistake. When it comes to compliance, even one single error is not tolerable and the consequences can be severe.

CEO & Founder, Martin Markiewicz and COO & Co-Founder, Julia Markiewicz
CEO & Founder, Martin Markiewicz and COO & Co-Founder, Julia Markiewicz

Silent Eight has emerged as a pioneer in the financial crime compliance space. They achieved this by recognizing common challenges in the compliance space, namely using manual labor alone as a solution and relying on statistical methods that rely on risk weighting and scoring.

Which is why Silent Eight’s approach is to investigate every alert. Their AI allows this to be a possibility without compromising accuracy or speed and without scalability limitations. A technique which has proven to be a great success for the firm over the years.

Showing no signs of slowing down, Silent Eight’s success is skyrocketing at an outstanding rate. As their innovative services continue to transform the lives of many, the firm is growing the business, and their team, to meet the needs of clients and support their global growth. Looking ahead to what the future holds, Silent Eight is set to release transaction monitoring by Q4 of 2020 alongside their current award-winning solutions. The future looks bright for Silent Eight and we are excited to see what the team accomplishes in the years to come.

World Trade Centre Accra Partners with Global RegTech Silent Eight to Strengthen Capacity of African Financial Sector for Fighting Financial Crime

A full-day session to identify new cyber threats facing Ghana and the West African sub-region in the midst of the global pandemic will take place 27 August 

Accra, Ghana: The World Trade Centre, Accra (WTC-Accra) announced today that it will assemble a diverse, global faculty of thought-leaders and innovators to examine the changing paradigms of financial crime, and specifically how digital technology offers new solutions to manage and eliminate these challenges. The goal of the one-day session, scheduled for 27 August at 2:00pm GMT, is to offer African governments and regulators new opportunities to improve their countries’ international financial ratings.

The session is the first of its kind and represents a move by the WTC Accra to focus on technological advancements that will both safeguard and improve Africa’s status in the global financial marketplace. Silent Eight was selected as a technology partner for the session because of its award-winning AI that enables banks and other financial institutions to successfully manage their AML and compliance obligations. 

“The recent COVID-19 pandemic has accelerated digitization processes that were already in motion around the world. Now more than ever, companies and nations rely heavily on completely virtual platforms to execute financial transactions of varying complexity and volume,” said WTC, Accra Executive Director, Edem Kofi Yevutsey.

“The increasing prominence of African economies and their integration into all facets of the global financial system mean that if African countries are not adequately prepared to deal with some of the challenges facing the global financial system, they could become the link that weakens the entire system.”

Moderated by former Moody’s Compliance Officer and securities market investigator Scott McCleskey, the roundtable will feature Sampson Akligoh, the Director of Financial Services, Ministry of Finance, Ghana, Matthew Leaney, Chief Revenue Officer of Silent Eight, Marcus Swanepoel, Business Solutions Manager of Temenos, Middle East and Africa, and George Nkrumah, Head of Financial integrity, Bank of Ghana.

The webinar will showcase some of the latest innovation and technology such as Artificial Intelligence (AI), data science, and machine learning that may be used to combat international financial crimes, cyber fraud and money laundering.  

To register your interest or learn more, visit:

About WTC Accra: The Accra World Trade Centre Limited Is a Private Limited Liability Company duly registered under the laws of Ghana and licensed by The World Trade Center Association (WTCA). The mission is to serve as a doorway to a world of global trade opportunities for companies in Ghana and the West African sub-region as well as a soft-landing pad for international commercial interests seeking to take advantage of exciting opportunities in Africa.
About Silent Eight: Silent Eight is an award-winning RegTech that helps financial institutions manage their compliance and risk obligations. The company leverages artificial intelligence and machine learning to improve their name, transaction, and entity screening processes; weed out money laundering and terrorist financing; reduce manpower and compliance risks; and enable better decision making. They are currently used by Tier 1 global banks and have regulatory approval in over 70 markets.

Fintech Interview with Founder and CEO, Silent Eight – Martin Markiewicz

Martin Markiewicz from Silent Eight discusses the integration of alert investigation into the case management processes of financial service providers, AI, and offers advice to other startups.

1. Tell us about your role at Silent Eight?

As a company, we have a mission to fight financial crime. We want to help the “good guys” win the fight against all the bad actors that are trying to enter the global financial system. We can do this by giving the good guys (banks, financial institutions, etc) the best tools possible so they can win and ultimately make the world safer. Our vision is to change what is happening around the world and to do so through innovative and advanced technology.

My role at Silent Eight is to always drive toward this vision, to make sure that we are creating this technology and that we never stop. That we never say “my job here is done,” but that we continue to put a lot of effort into research and development (R&D) and continue to equip the good guys to win the fight.

The other part of my role is to make sure that we take the innovations we create and not just mark them as “done” or shelve them and leave them alone. To make our vision come to life, all financial institutions around the world must use this technology. We have to reach them, prove the benefits coming out of using the technology, and then support them when they start using it.

2. Can you tell us your journey into this market?

We were very surprised that opportunities for someone like us in this market still existed when we started our research. When we looked at all the effort going into fighting financial crime and saw the incredible volume of work –across regulators, government, banks– these are institutions that are investing billions in technology and people. They are doing so much great work and making such a large impact, that we initially only hoped to improve their lives by maybe 5%.

We saw that there was room for an impact, but we imagined it to be small. However, when we started working hard and investing heavily on R+D with our first customers, (a global Tier 1 bank), what we discovered is that what can build and deliver has more than a 5%+ impact, but we can literally change the game. We can make things 500x, maybe even 5000x better. This is the impact we realized we could have and once we realized this, it was a no-brainer to continue on this journey.

3. How do you think technology is upgrading in the RegTech sector?

In our daily lives, all of us use more and more advanced technologies. – like google home, alexa, etc. And we’re using these regularly, to the point where we are hopeless without our smartphones and all the applications and cloud services that are plugged into our phones to connect with others, make better decisions, navigate terrain, etc. Right now we take these things for granted because they are so ingrained.

But the same adoption needs to happen when it comes to regulatory technology. We have to bridge the gap between what we’re doing in our home and what we’re doing at work in regards to the tools we have available. So that the advancement in our personal lives is part of financial crime regulation. Because why shouldn’t people fighting crime be able to have access to advanced AI that makes life easier? There is a natural path to leverage on all the research and experience that we’ve collected from the consumer market and places that turn out to be early adopters. We can use learnings (and not repeat mistakes) and try to apply them in the regtech sector. The caveat is doing this responsibly and in a transparent way.

4. How has application of AI technology empowered the financial ecosystem?

The financial ecosystem as a whole was always behind consumer technology and other sectors. It is heavily regulated and so change happens more slowly than in other areas of our industry.

I can’t speak to how AI has impacted the entire ecosystem, because my expertise is only in the way that it can impact anti-money laundering and the financial crime compliance sector. But, in this segment of the financial system, there is a tectonic shift in the way things were done not so long ago, to how the work is being done today with our help and the help of companies like ours.

5. Can you explain how integration of existing platforms of companies with Silent Eight can bring a major change to their due diligence processes?

Every time there is even a slight risk that something is suspicious, a responsible bank or financial institution needs to conduct a detailed investigation. All the evidence needs to be collected, so the institution can understand the entire situation and context. Then, based on the facts, laws, and internal policies, a decision needs to be made. We’ve created a machine that can learn how humans are actually doing these investigations, how they reason about it–the why and how of the decisions– liberates our customers and provides security for their institutions.

We not only are able to conduct and solve an entire alert investigation, but we do it transparently and directly in a client’s existing case management. Our findings are presented back in plain English so that there is never a question of how or why a decision was made. This enables automation, but with full human control and oversight. We make concerns around precision, consistency and volume a thing of the past.

6. Congratulations for being recognized among top 12 Fintechs in Aurexia’s Finlab Index 2020! Can you share with us what features of your solution led to this achievement?

Thank you, we were honored to be selected by Aurexia. We believe what led to the selection was that our solution is not only visionary, but viable, but it is different from other vendors. We are actually solving the problem. We continuously learn the best ways to conduct an investigation in order to make good decisions and provide the right arguments. All of this takes place within a design that is completely transparent. Whoever is in charge can see what the system is learning and has complete control over its decisioning. The supervisor is able to see the output in plain English to verify what was decided and why.

7. What advice would you like to give to the technology Start Ups?

There’s a quote I love that goes something like “the smartest people aren’t always the most successful, it’s the ones who never give up.”

The advice I would give is:

brace for a long journey with a lot of problems along the way. You will have a lot of assumptions that will be challenged, and a lot will be proven to not be true. Let go of your ego, adjust, listen to your customers. Go forward and don’t quit.

8. What is the Digital innovation in AI technology according to you that will mark 2020?

I can’t disclose any details yet, but by the end of 2020, we will publish a success story with one of our customers that will be game-changing for us and the industry. Stay tuned

9. What are the major developments you are planning, in recent time?

The short answer is: doing more of what we’re doing already. In 2020 we’ve already doubled in size. We’re growing very quickly and creating a lot of innovation at the same time. We are fortunate enough to be able to deploy this innovation in one of the biggest FIs in the world.

Every 3 months, when I sit down and look back at the previous quarter, I see that there are so many groundbreaking things we have achieved and a pipeline that is fast growing.

10. Can you tell us about your team and how it supports you?

We have an incredible team– people in the US, UK, Poland, and Singapore. And we have some of the smartest people in the world working with us. The team recently grew by a lot, with incredibly talented people that are aligned with our mission coming on board. In terms of team size and output, we are 2x bigger, but we are doing 10x more, it’s truly amazing.

AND! We’re hiring, check out our career page. We are constantly looking for new talent, especially for people who are passionate about using technology to stop bad actors.

11. Can you give us a glance of the applications you use on your phone?

I love Blinkist. It’s a cool app because it’s basically an executive summary for nonfiction books. The last one I listened to, today, on 2x speed, was “The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution” by Gregory Zuckerman. It’s a book about Jim Simons, Founder of Renaissance Technologies, the best quant hedge fund in the world that had returned more than 66 percent annualized returns over a 30-year span from 1988 to 2018 using math and models of the market. Jim cracked codes in the cold war and was a mathematics professor. It was an awesome story about someone who saw a problem and approached it in a completely different way than everyone else.. I’m a mathematician so Jim has always been an interesting guy for me.

Silent Eight Extends On-Demand AI Solution for Immediate Backlog Resolution and Ongoing KYC

The cloud-based offering will remain available through 2020 to meet customer demand

New York, New York: Silent Eight announced today that it will offer its powerful artificial intelligence (AI) solution for name, entity, and transaction alert adjudication on-demand, through the remainder of 2020. The decision comes in the wake of the current and ongoing pandemic, which has placed significant constraints and challenges on banks and financial institutions (FIs). These most notably include increasing and burdensome alert backlogs and unprecedented levels of cybercrime.1 The pandemic has also impacted the ability of both government and private sector institutions to meet their anti-money laundering and counter terrorist financing (AML/CFT) obligations.2 

Silent Eight’s AI has historically been installed on-premise for Tier 1 institutions3  to solve name, entity, and transaction alerts. Now the solution will be widely accessible to a broader market, and across more sectors, as a means of providing immediate and ongoing backlog relief, without requiring a long term commitment. 

The custom AI is configurable in as few as two (2) weeks via cloud deployment and offers a new way for banks and FIs to solve alerts in a scalable and agile manner in real time, regardless of external conditions such as COVID-19.

“Banks are already under so much pressure in ordinary times, especially as bad actors become more technologically savvy,” said Silent Eight CEO and Founder, Martin Markiewicz.

“But now, with the fast-changing global situation and most of us working remotely and moving to digital transactions, there’s heightened opportunity for financial cyber crime. With so much financial uncertainty fueling recessionary fears, the technology industry as a whole has a responsibility to protect the institutions that ensure  the global flow of capital — and, as a byproduct, the world — from those looking to wreak havoc.”

The on-demand AI is available immediately. Clients pay only for alerts solved, with no minimum volume commitment.

Features and benefits of the AI include:

To learn more, visit

About Silent Eight: We are a technology company whose mission is to enable financial institutions to fight global crime with the use of our AI.  Our name screening solution works with a client’s existing due diligence process to solve every alert and reduce regulatory risk.  We are currently used by top tier banks around the world.  


1 Will Douglas Heaven, “The Pandemic has changed how criminals hide their cash-and AI tools are trying to sniff it out,” MIT Technology Review, [website], 7 August 2020).

Robert Kim, “COVID-19 is raising AML compliance risks even higher,” Bloomberg Law Analysis, [website], (accessed 28 July 2020).
Thomas Bock, “Pandemic adding to banks’ alert backlog,” Thomson Reuters, [website],, (accessed 28 July 2020).

2 Financial Action Task Force (FATF), “COVID-19-related Money Laundering and Terrorist Financing Risks and Policy Responses,” FATF, [website], (accessed 26 July 2020)

3 “We’ve partnered with Regulatory Technology firm Silent Eight.” Standard Chartered Bank, 9 July 2018, [press release],

How to Use AI In Financial Services: An Interview with John O’Neill

This interview was conducted by Bernard Lunn, editor of The Daily Fintech.

John O’Neill is the SVP of Regional Sales, Western US and Canada for Silent Eight. Although he is now in sales, John began as an engineer, for example working on some of the early browser technology in Champaign Illinois and later at Motorola.

We are publishing a 5 part series on AI in Banking by Amber Sutherland, also of Silent Eight.

I have recently also been diving down some other AI rabbit holes, such as what Open AI released recently (GPT-3).

John is a practitioner at the front lines of deploying AI in financial services. So, he seemed like a good person to talk to.

Open AI and GPT-3 is general purpose bottom of the stack technology. I was keen to dig below the surface hype about AI to also look at the limitations and, within that, the practical applications today. In our Artificial Intelligence (AI) week on Daily Fintech in 2016 we wrote:

“This exemplifies the AI mantra that hard is easy and easy is hard.

4 years later this still seems to be true. This human’s reaction – “phew we are still needed a bit longer”
I started by asking John to tell us something about Silent Eight, starting with the name (a silent electric version of the V8 engine?). No. It is more to do with Silent Eight being founded in Singapore where 8 is a lucky number. I knew that from my years in Singapore and it is why our annual subscription price is $143 (add those 3 numbers to get 8).

John is based in Chicago and there are employees all over the world. As John put it – “we are where the where banks are”.

I then asked him three questions that concern people who work in finance:

Q1 how can Banks use AI to more efficiently comply with anti money laundering regulations?

I knew from my career selling to banks that you have to sell to an existential risk issue. Failing to comply with anti money laundering regulations is an existential risk to banks and can land executives in jail. So if you have a solution to that, the bankers will pay attention. That is why Silent Eight sells AI compliance solutions to banks.

I also knew from working with Fintech startups that there is a tradeoff between time/friction and security/compliance. You can design the most perfectly secure/compliant system that takes so long and is such a pain for honest customers that you lose your customers. So Silent Eight works hard to deliver solutions that are both compliant and fast.

Money Laundering is a massive business. A 2009 study estimates money laundering at about 2.7% of the global economy annually and If it were a country it would be in the Top 10 economies in the world, between France and Brazil (#7 and 8).

So we can expect a lot of creative intelligence applied to coming up with patterns that fool the AI compliance machines. John confirmed that AI is evolving fast and while today’s AI is not good at spotting new patterns we should expect next gen AI to do much better. Even today AI is very good at spotting bad actors in existing patterns. Replaying what we learned 4 years ago:

This exemplifies the AI mantra that hard is easy and easy is hard.

Fortunately humans are good at the latter. Freed from the grunt work by AI machines, they will have the time to spot those unknown new patterns.  John confirmed that once AI is taught a new pattern, it will track it it consistently, accurately and quickly. It won’t get fooled again by that pattern. The bad actors will have to apply a lot of creative intelligence to invent a new scheme (which they can only use one time).

Q2 How can investors use AI to find accounting fraud before the companies implode?

Silent Eight is focused on using a mixture of bank data and public data to pinpoint money laundering. Although accounting fraud isn’t strictly their problem domain, it’s not a big leap to see how the banks could use a similar approach to pinpoint accounting fraud.

The Investment Banking and Wealth Management part of the banks could profit from such a tool as it would benefit the Hedge Funds that they work with.

Market downturns surface a lot more frauds. As Warren Buffet puts it “only when the tide goes out can you see who was swimming naked”.  So there is a lot of money to be made/saved today in finding accounting fraud before the companies implode.

Think Enron, Madoff in past cycles and Wirecard (so far) in this cycle.

The data is out there in the public domain. That is what XBRL is all about and why we track that so closely.

Of course if the owners control the data, they also control the XBRL data. Most accounting frauds are perpetrated by people right at the top of the company.

Which brings us back to my hopeful vision of AI machines and humans working together. The AI machines look through millions of financial statements looking for patterns similar to Enron, Madoff, Wirecard and all the accounting frauds from the past. Meanwhile a few creatively intelligent humans, freed from the grunt work by AI machines,  slowly look for the new pattern where “something looks fishy” from the creative new fraudster.

Q3 How can financial education sites use AI to give consumers better early warning about scams?

This is fundamentally a business model issue. There is no obvious way to make money by saving millions of poor people from getting scammed. Technically it is the same solution of AI machines working with creatively intelligent humans.

Fortunately, as one learns by looking at Open AI, there are tech billionaires who will donate money to help AI to help humanity.

My big takeaway is that crooks will have to become so creative to beat the AI machine that they might as well apply that creative intelligence to something honest. They can invent a new scheme, but when they try replicating it they find the AI machine singing the Who song – won’t get fooled again. Once AI gets better the crooks won’t even be able to play those tricks once.

Compliance Time Episode 10: Silent Eight

This is a special episode as it’s not only the 10th episode for the past three months but also for the first time we are having more than one guest with us today. Our guests Martin and Matthew are both working at the award-winning technology company Silent Eight which mission is to stop financial crime. As you will hear today they are very passionate about financial crime prevention plus they are experts in Artificial Intelligence which is an amazing formula leading to the development of a solution that improves global financial institutions due dillige. 

One of our guests is Martin Markiewicz – the founder and CEO of Silent Eight. With an educational background in mathematics, Martin is a serial entrepreneur and self-described “problem solver”. Prior to Silent Eight, Martin launched several successful startups in Europe and Asia, including a hydropower startup that saw a successful IPO. With his 16 years of experience in software and artificial intelligence solutions covering a wide range of applications, Martin has taken the challenge of helping banks outsmart financial criminals and money launderers, who are gaming their transaction systems, head-on.

Also, we have Matthew Leaney – based in New York, he is the Chief Revenue Officer of Silent Eight. As CRO, he oversees all aspects of growth and is constantly seeking new avenues for Silent Eight’s award-winning AI to aid organizations in their fight against money laundering and financial crime. Matthew volunteers with a number of charities principally focused on advancing underprivileged youth.

What Keeps Money Launderers Up at Night?

If you’re laundering money or financing terrorism, what keeps you up at night?

Beyond the day-to-day intrigues of a life of crime, you have a money trail to worry about. Sure, you fear the sophisticated law enforcement and intelligence agencies with the power to track you, shut you down, and put you behind bars. But what about the thousands of watchful eyes observing your money as it flows through banks, casinos, real estate and other covert financial conduits? 

Some of those eyes belong to trained bank employees — BSA and AML analysts, Financial Crimes Investigators, Compliance Officers, and many others — tasked with enforcing regulations meant to prevent exactly what you’re doing. Still, those individuals only investigate cases that have been discovered, so you and your fellow criminals rely on the surveillance that’s meant to find you to be unsophisticated, burdensome, and technologically behind.

Prosecution for financial crime can come at you from a number of directions. It’s certainly true that many important cases are developed from whistleblowers and informants, undercover operations, and referrals from other domestic and foreign law enforcement agencies. 

But far and away the most fruitful investigative sources are the banks and other businesses that have a detailed view of financial transactions, and which submit Suspicious Activity Reports (SARs) and other forms to report potential financial crime. Financial investigations begin with these reports and end with convictions and the shutting down of networks.

Law enforcement, intelligence agencies and others rely on reporting entities to conduct effective surveillance for financial crime and produce high-quality reports. Criminals and terrorists rely on them to fail.

‘Surveillance’ sounds easy, doesn’t it? Cops on CSI and Boesh do it all the time. It seems almost exciting. Banks see all the transactions, so creating and maintaining a system to flag suspicious activity should be pretty straightforward. 

But, of course, it isn’t. The problem isn’t simply sharpening your methods until they find every illicit activity hiding among those transactions you thought were harmless (in AML parlance, a ‘false negative’), but the much bigger problem of handling the mountain of alerts generated when you turn a hyper-sensitive process like that loose on the millions of transactions a bank typically handles each month (the ‘false positives.’) Every one of the false positive alerts has to be painstakingly investigated and cleared — and the more thorough and exacting your AML process is, the more of them you generate.

And, on top of the normal caseload, consider how the current global pandemic has created an even bigger backlog for banks — both with stimulus payment programs that generate alerts and by disrupting the normal operations banks use to deal with them.

You can see how artificial intelligence (AI) and other forms of technology are fast becoming very compelling. Properly used, AI applies advanced logic on a consistent basis to spot hidden transactions and reduce false positives – more wheat, less chaff. 

Just as importantly, an AI learns on the job and learns quickly. As analysts review the output from the AI, and either validate or reject it, that feedback becomes critical inputs in the AI model — part of its continuing education, as it were — and it rapidly adjusts its triggers and thresholds accordingly. 

In doing so, AI integrates the best of both worlds, marrying technology’s ability to deploy complex logic across large sets of data rapidly and effectively, with human judgment and the ability to make decisions in situations lacking full clarity.

This doesn’t just improve the alert-generation stage, but also the investigative process. SARs are the primary means of passing information to law enforcement, and the quality of that reporting is critical. AI allows the analyst to bring multiple sources of data to bear — on the client, the counterparty, and the account’s transaction history — so that the decision to file a SAR is fully supported by the evidence, not just a single red flag. 

It also dramatically reduces the time taken to produce the SAR, and ensures that the report is more detailed and thorough, giving the investigator a better head-start on the investigation.

AI is more than just a pathway for financial institutions to become more efficient, manage risk better, and make better use of resources. By enhancing the quality and frequency of reporting to national Financial Intelligence Units and law enforcement, it is a critical element in the global effort to combat terrorism financing, money laundering, and the underlying crimes they fund. 

And it guarantees nothing but sleepless nights for criminals trying to exploit the financial system.

This article was contributed by John O’Neill, Silent Eight

John O’Neill has worked in the tech industry, specifically AI and machine learning, for over 25 years and holds a PhD in Chemical Engineering.

Gaming the System

If you’re trying to get from Point A to Point B without getting caught by the authorities, you’re likely to head for the backroads where there are fewer police than on the highway. For the same reason, an increasing volume of illicit financial flows – money laundering, terrorist financing, and sanctions evasion – has been moving from the highways of the traditional financial system to the backroads of the casinos and gaming industry.

Casinos and gaming are generally grouped together as a sector of anti-money laundering / counter-terrorist financing (AML/CTF) activity, but they cover a range of businesses. In addition to physical casino facilities, on-line gambling is a growing sector of activity. Sports betting can be done at the venue, at a licensed betting shop, online, or even at casinos. Lastly, on-line video games using in-game currencies are a rising source of activity as criminals and terrorists seek to avoid the well-trodden path of financial institutions.

Certain challenges are common across the sector- the need for near real-time screening and transaction monitoring; the transfer of value into a non-traditional currency (chips or in-game virtual currencies) and the cross-border nature of clients and transactions. Taken together, these issues create challenges that are too complex to be addressed by manual processes.


Casinos are the most mature sector of the casinos and gaming group, with well-established typologies and comparatively well-developed regulatory requirements. At its most basic, laundering money through a casino involves bringing in cash, purchasing chips or credit for play at the casino, and “cashing in” with a check from the casino which can then be deposited into the financial system as “clean money.” A major advantage of using a casino is that large sums can be laundered at once, since it is not unusual for “VIP” customers to spend hundreds of thousands of dollars.

Two prominent casino typologies are worth noting, both of which involve criminal organizations in China. In the Vancouver model, wealthy Chinese gamblers deposit funds in the local accounts of criminal organizations in China, and in return those organizations provide funds in Canada to the gamblers once they arrive in Vancouver – these funds are the proceeds of criminal activity in and around Vancouver,  and are held in local Canadian banks controlled by the criminals. The gamblers use these funds to purchase chips in the Vancouver casinos, then cash them in and receive a check from the casino. They deposit the check in the same (or different) criminally-controlled banks in Canada. The funds are then wired back to China through a series of shell corporations, and then back to the underground banks in and around Vancouver. As the last step, the funds are typically used to buy local real estate.

The second typology involves travel junkets to casinos in Macau. In order to skirt Chinese currency restrictions, a Chinese businessman (or criminal) will pay a large sum of money in Chinese currency – for example, $100,000 worth of renminbi – to a junket operator. In return, he or she will receive airfare, hotel accommodation, and a credit – perhaps $70,000 – at the casino. After using some of the money gambling, the businessman cashes out in US dollars or another currency and has thus laundered the money without directly sending it through the financial system.

Detecting these and other typologies can be done from an analysis of transactions (e.g. detecting a player who buys chips, does little or no gambling, and then leaves with the proceeds check shortly after arriving), but these typologies also offer the opportunity for screening solutions. Because the screening must be done in near-real time, modern technology is required since manual processes would take too long and would be prone to error.  

In most jurisdictions today, casinos screen against lists of individuals known or suspected of criminal links and against Politically Exposed Persons (PEPs); rules in Canada and Macau have been tightened in the last few years with respect to Customer Due Diligence and Enhanced Due Diligence (EDD) by casinos in their jurisdictions.

Online gambling and betting

Of course, casino games and sports betting occur online as well as in physical locations, and this makes the AML/CTF challenges even more daunting. As is the case with online banking, the onboarding and CDD processes are not done in person, and potential customers don’t want to wait days for the process to be completed and the account opened. The only way to have processes that are both robust and quick is to leverage Artificial Intelligence (AI) and other leading technologies. With these technologies, online casinos and betting sites can maintain continuously updated lists of sanctioned individuals and PEPs that can be checked 24/7 to accommodate the operation of the business across time zones. Since money deposits, transfers and withdrawals are done on line, technology must also be deployed to check any third parties and to analyze transactions for indications of money laundering, terrorist financing or sanctions evasion.

Online Gaming

Online gaming is a route for money laundering and terrorist financing that is overlooked by most people, but not by the criminals and terrorists. When you think of it, many games allow and encourage players to buy in-game currencies that they can use to purchase items or premium content within the game.  Criminals can then sell these to other players for real currency or they can sometimes receive a refund for purchases they claim were a mistake. In either case, the funds initially paid into the game come out as money from a legitimate source, an essential element of the layering stage of the money laundering process.

Unlike casinos, you can’t move hundreds of thousands of dollars through a single transaction in a video game. Moving appreciable amounts of money requires multiple transactions, and this can be detected by AI. Additionally, AI can spot the patterns produced by the transactions and as player profiles deviate from expected levels of activity.

Addressing the Challenge

The growth of money laundering, terrorist financing and sanctions evasion through casinos and gambling reflects the need for criminals to avoid the common and closely-watched paths. Having said that, organizations from FATF to national regulators to individual businesses are increasing their focus, expanding their requirements, and raising their expectations with respect to how the sector is monitored. There remains a lot of catching up to do, but using the best technologies to create effective processes that are integrated, streamlined, and smart can help these businesses reduce their exposure to criminals and their risk to regulatory sanctions.

About Andrew Fenton: Andrew (Andy) is responsible for Corporate and Non-bank financial institutions across EMEA APAC. He began his career in Fintechs, then shifted to Corporate Banking, and occupied coverage and leadership positions at JP Morgan Chase, Bank of America and Barclays Bank. He is currently SVP of Sales for Silent Eight. Follow him on LinkedIn.